Insights · Security

What useful AI security findings look like

The evidence, reporting, and retesting that turn an assessment into work your team can act on.

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Two readers, two deliverables

The engineer fixing a permission boundary needs different detail from the director deciding what to fund. Our assessment produces a technical findings report and an executive summary, with a shared account of the scope and the results.

The technical report identifies each affected resource or AI path, the evidence, and the steps needed to reproduce the result. The executive summary explains what the system can reach, what the findings mean for the business, and what needs attention first.

What each finding needs

A specific observation
Name the resource, setting, account, and configuration tested. Separate an observed failure from a plausible path that could not be verified.
Reproduction and evidence
Record the inputs, permission tier, and resulting action or disclosure. Include enough detail for your engineers to check the finding without exposing unnecessary sensitive data.
Business impact and priority
Explain what the affected system can read or do and who could be affected. Sequence remediation by risk and effort rather than leaving a list of unranked findings.
A practical fix
Identify the permission, configuration, application control, or design change needed. Give the team a way to verify that the change addresses the finding.
Applicable references
Record relevant OWASP identifiers or cloud baselines and their editions. Map evidence to the reporting framework agreed with your team without presenting the assessment as a certification.

Be explicit about coverage and limits

An architecture review, adversarial AI test, conventional penetration test, and compliance audit answer different questions. A useful report says which work was performed, which systems were excluded, and what remains unverified.

We prefer staging that resembles production in the ways that matter: permission scopes, integrations, and representative data. If those conditions cannot be reproduced, we document the gap. Any limited production testing is agreed in writing before it begins.

Framework mapping helps your security and governance teams use the evidence. It does not guarantee that an auditor will accept it, establish compliance, or replace a certification process.

Critical findings should not wait for the report

A standard engagement runs through kickoff, cloud review, AI testing, and reporting over four weeks. We escalate critical findings within 24 hours rather than save them for the final readout. The walkthrough, access provisioning, and draft review are the main demands on your team.

The readout is a working conversation. Your engineers need to confirm that the recommended fix is practical, and leadership needs to understand which decisions or resources the remediation requires.

Retest the changes that affect the result

A finding describes the configuration that was tested. A new model, prompt, retrieval corpus, permission set, or integration can change the behavior without changing the visible interface.

We leave repeatable AI cases that your engineers can run as the system changes. Those cases protect against known failures; they do not replace examining newly introduced tools or trust boundaries. Retesting should follow material changes to the system as well as remediation of the original findings.

The outcome is a record your team can act on now and compare against later. You should be able to explain what was tested, what broke, what was fixed, and what still needs attention.

Tell us what it can reach

Describe your AI system and what it connects to. We will help you work out whether an assessment is worth doing.